Please use this identifier to cite or link to this item: http://cmuir.cmu.ac.th/jspui/handle/6653943832/76427
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dc.contributor.authorChawis Boonmeeen_US
dc.contributor.authorAuttharat Kosayanonen_US
dc.contributor.authorImjai Chitapanaruxen_US
dc.contributor.authorChompoonoot Kasemseten_US
dc.date.accessioned2022-10-16T07:09:53Z-
dc.date.available2022-10-16T07:09:53Z-
dc.date.issued2021-12-01en_US
dc.identifier.issn22346473en_US
dc.identifier.issn15987248en_US
dc.identifier.other2-s2.0-85099803621en_US
dc.identifier.other10.7232/iems.2020.19.4.758en_US
dc.identifier.urihttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85099803621&origin=inwarden_US
dc.identifier.urihttp://cmuir.cmu.ac.th/jspui/handle/6653943832/76427-
dc.description.abstractRadiotherapy service has seen a spur of interest in the health care system. Many cancer centers aim to develop and enhance radiotherapy service to support the increasing demand. Because Thailand is a developing country, some cancer centers still have limited resources, both staff and machinery, while the number of cancer patients in Thailand has increased every year. To enhance the operational efficiency of radiotherapy service, this research aims to propose an integrated simulation approach and theory of constraints (TOC) approach for increasing radiotherapy service capability in Thailand. As simulation and TOC were applied in the case study, the real bottlenecks were identified in each treatment room. Considering four treatment rooms, only two rooms were selected for improvement (Room 2 and Room 3) after the simulation. The eight proposed solutions concentrated on improving both human- and machine-related bottlenecks. The simulation experiments were conducted to evaluate each solution. The results presented the best solution as adding one technician to Room 3 and replacing the radiation machine in Room 2 with the same machine as in Room 3. With this solution, the number of patients served was increased by 12.32% from the current system. As for the investment needed, the benefit-cost ratio and payback period were calculated as 1.89 and 2.80 years, respectively, for this solution.en_US
dc.subjectEconomics, Econometrics and Financeen_US
dc.subjectSocial Sciencesen_US
dc.titleRadiotherapy service improvement: Simulation studyen_US
dc.typeJournalen_US
article.title.sourcetitleIndustrial Engineering and Management Systemsen_US
article.volume19en_US
article.stream.affiliationsChiang Mai Universityen_US
Appears in Collections:CMUL: Journal Articles

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